SlideShare a Scribd company logo
MPEG-7 Services  in Community Engines   Ralf Klamma   Leuven, Belgium  October 26, 2007
Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Multimedia Metadata Community Our Goals  ,[object Object],[object Object],[object Object],[object Object],[object Object]
Multimedia Metadata Community Our Goals  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Multimedia Metadata Community Partners  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Multimedia Metadata Community – Events ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Multimedia management  features of MPEG-7 Basis  Schema  Links&Media  Basic  Basic tools  localization  tools  data types [IEEE 02] User interaction User preferences Usage History Navigation  & Access Index Views Variations Content organization  Collections  Models   Creation & Production Content Management   Media  Usage Content description Structural aspects  Semantic aspects
XML Schema Language -  Descriptors, DS, and DDL DDL DS DS DS D D D D DS D D Structural aspects of domains Domain spec.  MPEG-7 extension MPEG-7 descriptor or DS non MPEG-7 descriptor or DS
Schema Tools Basis  Schema  Links&Media  Basic  Basic tools  localization  tools  data types [IEEE 02] User interaction User preferences Usage History Navigation  & Access Index Views Variations Content organization  Collections  Models   Creation & Production Content Management   Media  Usage Content description Structural aspects  Semantic aspects
MPEG-7 Root Element
MPEG-7 Top Elements
[object Object],Basis Data Type –  Graphs D B E A C r3 r3 r2 r1 r1 r4 <Graph> <Node id=&quot;A&quot; /><Node id=&quot;B&quot; />   <Node id=&quot;C&quot; /><Node id=&quot;D&quot; />   <Node id=&quot;E&quot; /> <Relation type= =&quot;#r1&quot; source= &quot;#A&quot;  target= =&quot;#B&quot; />  <Relation type= =&quot;#r2&quot; source= &quot;#A&quot;  target= =&quot;#C&quot; />  <Relation type= =&quot;#r3&quot;  source= &quot;#B&quot;  target= =&quot;#D&quot; />  <Relation type= =&quot;#r3&quot; source= &quot;#C&quot;  target= =&quot;#D&quot; />  <Relation type= =&quot;#r4&quot; source= &quot;#B&quot;  target= =&quot;#E&quot; />  <Relation type= =&quot;#r1&quot; source= &quot;#E&quot;  target= =&quot;#A&quot; />  </Graph>
Annotations <TextAnnotation> <StructuredAnnotation> <Who><Name>Spain</Name</Who> <Where><Name>AC</Name></Where> <When><Name>Mar15</Name></When> </StructuredAnnotation> </TextAnnotation> Structured Annotation <TextAnnotation> <KeywordAnnotation> <Keyword>score</Keyword> <Keyword>Sweden</Keyword> <Keyword>Spain</Keyword> </KeywordAnnotation> </TextAnnotation> Keyword Annotation <TextAnnotation xml:lang=&quot;en-us&quot;> This is a nice apartment.   </ TextAnnotation >   <TextAnnotation xml:lang=&quot;en-uk&quot;> This is a nice flat.  </TextAnnotation > Free Text Annotation
Textual Annotations Score Spain A goal Sweden Against Governer Dependent Governer Dependent Dependent Dependent Dependency structure for &quot;Spain scored a goal against Sweden“
Content  Management and Description Basis  Schema  Links&Media  Basic  Basic tools  localization  tools  data types [IEEE 02] User interaction User preferences Usage History Navigation  & Access Index Views Variations Content organization  Collections  Models   Creation & Production Content Management   Media  Usage Content description Structural aspects  Semantic aspects
Content Structures –  Segment Entities Räumliche und zeitliche Segmente
Content Structures –  Segment Entities Raum-zeitliches Segment
Content Structures –  Segment Decomposition Segment decomposition
Content Structures –  Structural Relations ,[object Object],[object Object],[object Object],[object Object],  Typed normative structural relations in MPEG-7 Precedes, follows, meets, metBy, overlaps, overlappedBy, contains, during, strictContains, stricrtDuring, starts, startedBy,  finishes, finishedBy, coOccurs, contiguous, sequential, coBegin, coned, parallel, overlapping.   Temporal   South, North, West, East, Northwest, Northeast, Southwest, Southeast, Left, Right, Below, Above, Over, Under.   Spatial   Normative Relations Type
Example for Segmentation Tree Foreground Background SR1: · Creation,  Usage meta information · Media  description · Textual  annotation · Color  histogram,  Texture SR2: · Shape · Color  Histogram · Textual  annotation SR6: · Color  Histogram · Textual  annotation SR5: · Shape · Textual  annotation SR4: · Shape · Color  Histogram · Textual  annotation SR3: · Shape · Color  Histogram · Textual  annotation
Example for Content Semantics Segment Tree Shot1  Shot2 Shot3 Segment 1 Sub-segment 1 Sub-segment 2 Sub-segment 3 Sub-segment 4 segment 2 Segment 3 Segment 4 Segment 5 Segment 6 Segment 7 Semantic DS (Events) • Introduction • Summary • Program logo • Studio • Overview • News Presenter • News  Items • International • Clinton Case • Pope in Cuba • National • Twins • Sports • Closing Time Axis
Putting it all together
Navigation and Access Basis  Schema  Links&Media  Basic  Basic tools  localization  tools  data types [IEEE 02] User interaction User preferences Usage History Navigation  & Access Index Views Variations Content organization  Collections  Models   Creation & Production Content Management   Media  Usage Content description Structural aspects  Semantic aspects
Summaries – Keyframes Original Conten (represented by Keyframes) and highlighted  summary content MovieClip1 Summary MovieClip2 MovieClip3
Hierarchical Summary Hierarchical Summary Summary Theme  List Summary  SegmentGroup Summary Segment 0, 1 1, * 1, * 0, *
Sequential Summary Sequential Summary Visual SummaryComponent  Audio SummaryComponent  Textual SummaryComponent  0, * 0, * 0, *
Views Multimedia program Multimedia program View Filtering Partition Region View Signal Source Signal  View graphs View trees View sets Source Target View decompositions
Views – Space  and Frequency Graph F F F S S S
Variations Variation Set Multimedia program Variation Fidelity Relationship Priority Multimedia program Variation Fidelity Relationship Priority Multimedia program Image Video Video Source Variation Variation
Content Organization Basis  Schema  Links&Media  Basic  Basic tools  localization  tools  data types [IEEE 02] User interaction User preferences Usage History Navigation  & Access Index Views Variations Content organization  Collections  Models   Creation & Production Content Management   Media  Usage Content description Structural aspects  Semantic aspects
Collections Collection (abstract) Segment collection Content collection Descriptor collection Concept collection Mixed collection Collection structure
Content Collections and  Collection Structure Different collection can be combined according to their collection structure Collection A Collection B Collection C R ac R bc R ab
Models Model (abstract) Probability Model Analytic Model Cluster Model Classification Model ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Cluster Model – Relevance Feedback After relevant content is marked by the user, the retrieval system can deliver more precise content clusters
State Transition Models State Transition models can be used for summarizing or classifying transitions of events on the timeline of a video sequence Video sequence with events, e.g. staging of an actor A C B p ab p ac p bc p ca Label Scene A C B Event A Event B Event C
User Interaction Basis  Schema  Links&Media  Basic  Basic tools  localization  tools  data types [IEEE 02] User interaction User preferences Usage History Navigation  & Access Index Views Variations Content organization  Collections  Models   Creation & Production Content Management   Media  Usage Content description Structural aspects  Semantic aspects
Multimedia System with  User Interaction Content filter & search engine Content browsing engine User profiling  engine Local multimedia system Multimedia content description Multimedia content Multimedia content description Multimedia content description User  preferences User action history Other devices Content/service provider User
Usage History Usage history 1, * 0, * UserIdentifier User action history Observation period User action list ActionType Action data item User action ProgramIdentifier ActionTime 1, * 1, * 0, *
User Preferences User preferences UserIdentifier Browsing preferences Summary preferences Preference condition Filtering and  search  preferences Preference condition Classification preferences Creation preferences Source preferences 0, * 0, * 0, * 0, * 0, * 0, * 0, * 0, * 0, *
Mapping Usage Hisotries on  User Preferences Usage history  description UserAction Program ID 1 UserAction Program ID 2 Content description Program ID 1 Title 1 Genre A Content description Program ID 2 Title 2 Genre B User preference description Classification  Preferences Genre A preference Value a Genre B preference Value b
Visual & Audio Descriptors ,[object Object],[object Object],[object Object],[object Object]
Color Space Descriptor I
Color Space Descriptor II
Texture Browsing Descriptor I
Texture Browsing Descriptor II Directions of textures:
Edge Histogram Descriptor
Overview Shape Descriptors ,[object Object],[object Object],[object Object],[object Object],Special type: Multiview Type  Combination of Multiview and SD for 3D Object description (3D Form derived from multiple perspective 2-D views)  Region-based notion  of similarity Contour-based notion  of similarity
Region Based SD ,[object Object],[object Object]
Contour Based SD ,[object Object],[object Object]
Motion Descriptors
Multimedia Community Hosting ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
LAS – Architecture Overview Data Sources Context-Aware Services Community Engine WWW MPEG-7  Services Context  Services User Manager Map  Services Storytelling Service Object  Manager (Mobile) Interfaces Session Manager SNA  Tools Multimedia Processor Multimedia Annotation Multimedia Extractor Multimedia Adaptation Multimedia Player Metadata Databases Connectors: HTTP, SOAP Multimedia Repository Media Creation Media Search Media Tagging Semantic Browsing Mashups Automatic Discovery & Configuration Multimedia Input Data  Access Multimedia Repository Multimedia Repository Invoking services Data flows
Data Sources Context-Aware Services Community Engine WWW MPEG-7  Services Context  Services User Manager Map  Services Storytelling Service Object  Manager (Mobile) Interfaces Session Manager SNA  Tools Multimedia Processor Multimedia Annotation Multimedia Extractor Multimedia Adaptation Multimedia Player Metadata Databases Connectors: HTTP, SOAP Multimedia Repository Media Creation Media Search Media Tagging Semantic Browsing Mashups Automatic Discovery & Configuration Multimedia Input Data  Access Multimedia Repository Multimedia Repository MPEG-7  Services Context  Services Media Creation GPS-augmented multimedia creation Multimedia GIS Map  Services Media Search Semantic Browsing MPEG-7  Services Context aware multimedia GIS Map  Services Media Search Semantic Browsing Context  Services MPEG-7  Services MPEG-7 multimedia tagging and commsonomy SNA  Tools Media Search Media Tagging MPEG-7  Services MPEG-7  Services Context  Services Media Search Semantic Browsing MPEG-7 enabled context aware multimedia search MPEG-7  Services Storytelling Service Semantic Browsing Non-linear digital storytelling Storytelling Service Storytelling on the ipod Context aware multimedia search Media Search MPEG-7  Services Context  Services
MPEG-7 LAS Service Framework ,[object Object],[object Object],[object Object],[object Object],[object Object]
Image/Video Tagging with NMV ,[object Object],[object Object],[object Object],[object Object]
Virtual Campfire
Conclusions & Outlook ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

More Related Content

Similar to MPEG-7 Services in Community Engines

A Mobile Audio Server enhanced with Semantic Personalization Capabilities
A Mobile Audio Server enhanced with Semantic Personalization CapabilitiesA Mobile Audio Server enhanced with Semantic Personalization Capabilities
A Mobile Audio Server enhanced with Semantic Personalization CapabilitiesUniversity of Piraeus
 
A Personalized Audio Web Service using MPEG-7 and MPEG-21 standards
A Personalized Audio Web Service using MPEG-7 and MPEG-21 standardsA Personalized Audio Web Service using MPEG-7 and MPEG-21 standards
A Personalized Audio Web Service using MPEG-7 and MPEG-21 standardsUniversity of Piraeus
 
A Personalized Audio Server using MPEG-7 and MPEG-21 standards
A Personalized Audio Server using MPEG-7 and MPEG-21 standardsA Personalized Audio Server using MPEG-7 and MPEG-21 standards
A Personalized Audio Server using MPEG-7 and MPEG-21 standardsUniversity of Piraeus
 
[2015/2016] Introduction to software architecture
[2015/2016] Introduction to software architecture[2015/2016] Introduction to software architecture
[2015/2016] Introduction to software architectureIvano Malavolta
 
IRJET- Multimedia Summarization and Retrieval of News Broadcast
IRJET- Multimedia Summarization and Retrieval of News BroadcastIRJET- Multimedia Summarization and Retrieval of News Broadcast
IRJET- Multimedia Summarization and Retrieval of News BroadcastIRJET Journal
 
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...IRJET Journal
 
Personalized Multimedia Web Services in Peer to Peer Networks Using MPEG-7 an...
Personalized Multimedia Web Services in Peer to Peer Networks Using MPEG-7 an...Personalized Multimedia Web Services in Peer to Peer Networks Using MPEG-7 an...
Personalized Multimedia Web Services in Peer to Peer Networks Using MPEG-7 an...University of Piraeus
 
Community-Aware Semantic Multimedia Tagging – From Folksonomies to Commsonomies
Community-Aware Semantic Multimedia Tagging –From Folksonomies to CommsonomiesCommunity-Aware Semantic Multimedia Tagging –From Folksonomies to Commsonomies
Community-Aware Semantic Multimedia Tagging – From Folksonomies to CommsonomiesRalf Klamma
 
CREW VRE Release 5 - 2009 May
CREW VRE Release 5 - 2009 MayCREW VRE Release 5 - 2009 May
CREW VRE Release 5 - 2009 MayMartin Turner
 
The path to an hybrid open source paradigm
The path to an hybrid open source paradigmThe path to an hybrid open source paradigm
The path to an hybrid open source paradigmJonathan Challener
 
A Distributed Audio Personalization Framework over Android
A Distributed Audio Personalization Framework over AndroidA Distributed Audio Personalization Framework over Android
A Distributed Audio Personalization Framework over AndroidUniversity of Piraeus
 
[2017/2018] Introduction to Software Architecture
[2017/2018] Introduction to Software Architecture[2017/2018] Introduction to Software Architecture
[2017/2018] Introduction to Software ArchitectureIvano Malavolta
 
IRJET- Deep Web Searching (DWS)
IRJET- Deep Web Searching (DWS)IRJET- Deep Web Searching (DWS)
IRJET- Deep Web Searching (DWS)IRJET Journal
 
[2016/2017] Introduction to Software Architecture
[2016/2017] Introduction to Software Architecture[2016/2017] Introduction to Software Architecture
[2016/2017] Introduction to Software ArchitectureIvano Malavolta
 
Modular Documentation Joe Gelb Techshoret 2009
Modular Documentation Joe Gelb Techshoret 2009Modular Documentation Joe Gelb Techshoret 2009
Modular Documentation Joe Gelb Techshoret 2009Suite Solutions
 
Introduction to SOFTWARE ARCHITECTURE
Introduction to SOFTWARE ARCHITECTUREIntroduction to SOFTWARE ARCHITECTURE
Introduction to SOFTWARE ARCHITECTUREIvano Malavolta
 
My project experiences
My project experiences My project experiences
My project experiences Sung Eob Lee
 
Scalable architectures for phenotype libraries
Scalable architectures for phenotype librariesScalable architectures for phenotype libraries
Scalable architectures for phenotype librariesMartin Chapman
 

Similar to MPEG-7 Services in Community Engines (20)

A Mobile Audio Server enhanced with Semantic Personalization Capabilities
A Mobile Audio Server enhanced with Semantic Personalization CapabilitiesA Mobile Audio Server enhanced with Semantic Personalization Capabilities
A Mobile Audio Server enhanced with Semantic Personalization Capabilities
 
A Personalized Audio Web Service using MPEG-7 and MPEG-21 standards
A Personalized Audio Web Service using MPEG-7 and MPEG-21 standardsA Personalized Audio Web Service using MPEG-7 and MPEG-21 standards
A Personalized Audio Web Service using MPEG-7 and MPEG-21 standards
 
A Personalized Audio Server using MPEG-7 and MPEG-21 standards
A Personalized Audio Server using MPEG-7 and MPEG-21 standardsA Personalized Audio Server using MPEG-7 and MPEG-21 standards
A Personalized Audio Server using MPEG-7 and MPEG-21 standards
 
Domain specific modeling for mobile and io t apps
Domain specific modeling for mobile and io t appsDomain specific modeling for mobile and io t apps
Domain specific modeling for mobile and io t apps
 
[2015/2016] Introduction to software architecture
[2015/2016] Introduction to software architecture[2015/2016] Introduction to software architecture
[2015/2016] Introduction to software architecture
 
IRJET- Multimedia Summarization and Retrieval of News Broadcast
IRJET- Multimedia Summarization and Retrieval of News BroadcastIRJET- Multimedia Summarization and Retrieval of News Broadcast
IRJET- Multimedia Summarization and Retrieval of News Broadcast
 
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...
IRJET- Towards Efficient Framework for Semantic Query Search Engine in Large-...
 
Personalized Multimedia Web Services in Peer to Peer Networks Using MPEG-7 an...
Personalized Multimedia Web Services in Peer to Peer Networks Using MPEG-7 an...Personalized Multimedia Web Services in Peer to Peer Networks Using MPEG-7 an...
Personalized Multimedia Web Services in Peer to Peer Networks Using MPEG-7 an...
 
Community-Aware Semantic Multimedia Tagging – From Folksonomies to Commsonomies
Community-Aware Semantic Multimedia Tagging –From Folksonomies to CommsonomiesCommunity-Aware Semantic Multimedia Tagging –From Folksonomies to Commsonomies
Community-Aware Semantic Multimedia Tagging – From Folksonomies to Commsonomies
 
CREW VRE Release 5 - 2009 May
CREW VRE Release 5 - 2009 MayCREW VRE Release 5 - 2009 May
CREW VRE Release 5 - 2009 May
 
Sw Software Design
Sw Software DesignSw Software Design
Sw Software Design
 
The path to an hybrid open source paradigm
The path to an hybrid open source paradigmThe path to an hybrid open source paradigm
The path to an hybrid open source paradigm
 
A Distributed Audio Personalization Framework over Android
A Distributed Audio Personalization Framework over AndroidA Distributed Audio Personalization Framework over Android
A Distributed Audio Personalization Framework over Android
 
[2017/2018] Introduction to Software Architecture
[2017/2018] Introduction to Software Architecture[2017/2018] Introduction to Software Architecture
[2017/2018] Introduction to Software Architecture
 
IRJET- Deep Web Searching (DWS)
IRJET- Deep Web Searching (DWS)IRJET- Deep Web Searching (DWS)
IRJET- Deep Web Searching (DWS)
 
[2016/2017] Introduction to Software Architecture
[2016/2017] Introduction to Software Architecture[2016/2017] Introduction to Software Architecture
[2016/2017] Introduction to Software Architecture
 
Modular Documentation Joe Gelb Techshoret 2009
Modular Documentation Joe Gelb Techshoret 2009Modular Documentation Joe Gelb Techshoret 2009
Modular Documentation Joe Gelb Techshoret 2009
 
Introduction to SOFTWARE ARCHITECTURE
Introduction to SOFTWARE ARCHITECTUREIntroduction to SOFTWARE ARCHITECTURE
Introduction to SOFTWARE ARCHITECTURE
 
My project experiences
My project experiences My project experiences
My project experiences
 
Scalable architectures for phenotype libraries
Scalable architectures for phenotype librariesScalable architectures for phenotype libraries
Scalable architectures for phenotype libraries
 

More from Ralf Klamma

An Augmented Reality Framework for Gamified Learning
An Augmented Reality Framework for Gamified LearningAn Augmented Reality Framework for Gamified Learning
An Augmented Reality Framework for Gamified LearningRalf Klamma
 
The Legacy of ROLE - Where are we at the workplace?
The Legacy of ROLE - Where are we at the workplace?The Legacy of ROLE - Where are we at the workplace?
The Legacy of ROLE - Where are we at the workplace?Ralf Klamma
 
Gamification of Community Information Systems
Gamification of Community Information SystemsGamification of Community Information Systems
Gamification of Community Information SystemsRalf Klamma
 
The Legacy and the Future of Research Networks in Technology-Enhanced Learning
The Legacy and the Future of Research Networks in Technology-Enhanced LearningThe Legacy and the Future of Research Networks in Technology-Enhanced Learning
The Legacy and the Future of Research Networks in Technology-Enhanced LearningRalf Klamma
 
DevOpsUse for Large-Scale Social Requirements Engineering @ SIG WELL - EC-TEL...
DevOpsUse for Large-Scale Social Requirements Engineering @ SIG WELL - EC-TEL...DevOpsUse for Large-Scale Social Requirements Engineering @ SIG WELL - EC-TEL...
DevOpsUse for Large-Scale Social Requirements Engineering @ SIG WELL - EC-TEL...Ralf Klamma
 
Learning Analytics: Trends and Issues of the Empirical Research of the Years ...
Learning Analytics: Trends and Issues of the Empirical Research of the Years ...Learning Analytics: Trends and Issues of the Empirical Research of the Years ...
Learning Analytics: Trends and Issues of the Empirical Research of the Years ...Ralf Klamma
 
A Short Swim through the Personal Learning Pool
A Short Swim through the Personal Learning PoolA Short Swim through the Personal Learning Pool
A Short Swim through the Personal Learning PoolRalf Klamma
 
Scaling up digital learning support for smart workforce development in cluste...
Scaling up digital learning support for smart workforce development in cluste...Scaling up digital learning support for smart workforce development in cluste...
Scaling up digital learning support for smart workforce development in cluste...Ralf Klamma
 
Scaling Community Information Systems
Scaling Community Information SystemsScaling Community Information Systems
Scaling Community Information SystemsRalf Klamma
 
Technical Challenges for Realizing Learning Analytics
Technical Challenges for Realizing Learning AnalyticsTechnical Challenges for Realizing Learning Analytics
Technical Challenges for Realizing Learning AnalyticsRalf Klamma
 
Technology-Enhanced Learning at the Workplace – From islands of automation to...
Technology-Enhanced Learning at the Workplace – From islands of automation to...Technology-Enhanced Learning at the Workplace – From islands of automation to...
Technology-Enhanced Learning at the Workplace – From islands of automation to...Ralf Klamma
 
ACIS Annual Report 2014
ACIS Annual Report 2014ACIS Annual Report 2014
ACIS Annual Report 2014Ralf Klamma
 
Blueprint for Software Engineering in Technology Enhanced Learning Projects
Blueprint for Software Engineering in Technology Enhanced Learning ProjectsBlueprint for Software Engineering in Technology Enhanced Learning Projects
Blueprint for Software Engineering in Technology Enhanced Learning ProjectsRalf Klamma
 
Navigation Support in Evolving Communities by a Web-based Dashboard
Navigation Support in Evolving Communities by a Web-based DashboardNavigation Support in Evolving Communities by a Web-based Dashboard
Navigation Support in Evolving Communities by a Web-based DashboardRalf Klamma
 
Community Learning Analytics – A New Research Field in TEL
Community Learning Analytics – A New Research Field in TELCommunity Learning Analytics – A New Research Field in TEL
Community Learning Analytics – A New Research Field in TELRalf Klamma
 
Do Mechanical Turks Dream of Big Data?
Do Mechanical Turks Dream of Big Data?Do Mechanical Turks Dream of Big Data?
Do Mechanical Turks Dream of Big Data?Ralf Klamma
 
Advanced Community Information Systems Group (ACIS) Annual Report 2013
Advanced Community Information Systems Group (ACIS) Annual Report 2013Advanced Community Information Systems Group (ACIS) Annual Report 2013
Advanced Community Information Systems Group (ACIS) Annual Report 2013Ralf Klamma
 
Community Learning Analytics - Challenges and Opportunities - ICWL 2013 Invit...
Community Learning Analytics - Challenges and Opportunities - ICWL 2013 Invit...Community Learning Analytics - Challenges and Opportunities - ICWL 2013 Invit...
Community Learning Analytics - Challenges and Opportunities - ICWL 2013 Invit...Ralf Klamma
 
Keynote Learning Layers Developer Camp 2013
Keynote Learning Layers Developer Camp 2013Keynote Learning Layers Developer Camp 2013
Keynote Learning Layers Developer Camp 2013Ralf Klamma
 
Supporting Professional Communities in the Next Web
Supporting Professional Communities in the Next Web Supporting Professional Communities in the Next Web
Supporting Professional Communities in the Next Web Ralf Klamma
 

More from Ralf Klamma (20)

An Augmented Reality Framework for Gamified Learning
An Augmented Reality Framework for Gamified LearningAn Augmented Reality Framework for Gamified Learning
An Augmented Reality Framework for Gamified Learning
 
The Legacy of ROLE - Where are we at the workplace?
The Legacy of ROLE - Where are we at the workplace?The Legacy of ROLE - Where are we at the workplace?
The Legacy of ROLE - Where are we at the workplace?
 
Gamification of Community Information Systems
Gamification of Community Information SystemsGamification of Community Information Systems
Gamification of Community Information Systems
 
The Legacy and the Future of Research Networks in Technology-Enhanced Learning
The Legacy and the Future of Research Networks in Technology-Enhanced LearningThe Legacy and the Future of Research Networks in Technology-Enhanced Learning
The Legacy and the Future of Research Networks in Technology-Enhanced Learning
 
DevOpsUse for Large-Scale Social Requirements Engineering @ SIG WELL - EC-TEL...
DevOpsUse for Large-Scale Social Requirements Engineering @ SIG WELL - EC-TEL...DevOpsUse for Large-Scale Social Requirements Engineering @ SIG WELL - EC-TEL...
DevOpsUse for Large-Scale Social Requirements Engineering @ SIG WELL - EC-TEL...
 
Learning Analytics: Trends and Issues of the Empirical Research of the Years ...
Learning Analytics: Trends and Issues of the Empirical Research of the Years ...Learning Analytics: Trends and Issues of the Empirical Research of the Years ...
Learning Analytics: Trends and Issues of the Empirical Research of the Years ...
 
A Short Swim through the Personal Learning Pool
A Short Swim through the Personal Learning PoolA Short Swim through the Personal Learning Pool
A Short Swim through the Personal Learning Pool
 
Scaling up digital learning support for smart workforce development in cluste...
Scaling up digital learning support for smart workforce development in cluste...Scaling up digital learning support for smart workforce development in cluste...
Scaling up digital learning support for smart workforce development in cluste...
 
Scaling Community Information Systems
Scaling Community Information SystemsScaling Community Information Systems
Scaling Community Information Systems
 
Technical Challenges for Realizing Learning Analytics
Technical Challenges for Realizing Learning AnalyticsTechnical Challenges for Realizing Learning Analytics
Technical Challenges for Realizing Learning Analytics
 
Technology-Enhanced Learning at the Workplace – From islands of automation to...
Technology-Enhanced Learning at the Workplace – From islands of automation to...Technology-Enhanced Learning at the Workplace – From islands of automation to...
Technology-Enhanced Learning at the Workplace – From islands of automation to...
 
ACIS Annual Report 2014
ACIS Annual Report 2014ACIS Annual Report 2014
ACIS Annual Report 2014
 
Blueprint for Software Engineering in Technology Enhanced Learning Projects
Blueprint for Software Engineering in Technology Enhanced Learning ProjectsBlueprint for Software Engineering in Technology Enhanced Learning Projects
Blueprint for Software Engineering in Technology Enhanced Learning Projects
 
Navigation Support in Evolving Communities by a Web-based Dashboard
Navigation Support in Evolving Communities by a Web-based DashboardNavigation Support in Evolving Communities by a Web-based Dashboard
Navigation Support in Evolving Communities by a Web-based Dashboard
 
Community Learning Analytics – A New Research Field in TEL
Community Learning Analytics – A New Research Field in TELCommunity Learning Analytics – A New Research Field in TEL
Community Learning Analytics – A New Research Field in TEL
 
Do Mechanical Turks Dream of Big Data?
Do Mechanical Turks Dream of Big Data?Do Mechanical Turks Dream of Big Data?
Do Mechanical Turks Dream of Big Data?
 
Advanced Community Information Systems Group (ACIS) Annual Report 2013
Advanced Community Information Systems Group (ACIS) Annual Report 2013Advanced Community Information Systems Group (ACIS) Annual Report 2013
Advanced Community Information Systems Group (ACIS) Annual Report 2013
 
Community Learning Analytics - Challenges and Opportunities - ICWL 2013 Invit...
Community Learning Analytics - Challenges and Opportunities - ICWL 2013 Invit...Community Learning Analytics - Challenges and Opportunities - ICWL 2013 Invit...
Community Learning Analytics - Challenges and Opportunities - ICWL 2013 Invit...
 
Keynote Learning Layers Developer Camp 2013
Keynote Learning Layers Developer Camp 2013Keynote Learning Layers Developer Camp 2013
Keynote Learning Layers Developer Camp 2013
 
Supporting Professional Communities in the Next Web
Supporting Professional Communities in the Next Web Supporting Professional Communities in the Next Web
Supporting Professional Communities in the Next Web
 

Recently uploaded

ODC, Data Fabric and Architecture User Group
ODC, Data Fabric and Architecture User GroupODC, Data Fabric and Architecture User Group
ODC, Data Fabric and Architecture User GroupCatarinaPereira64715
 
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
 
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...Product School
 
UiPath Test Automation using UiPath Test Suite series, part 2
UiPath Test Automation using UiPath Test Suite series, part 2UiPath Test Automation using UiPath Test Suite series, part 2
UiPath Test Automation using UiPath Test Suite series, part 2DianaGray10
 
Powerful Start- the Key to Project Success, Barbara Laskowska
Powerful Start- the Key to Project Success, Barbara LaskowskaPowerful Start- the Key to Project Success, Barbara Laskowska
Powerful Start- the Key to Project Success, Barbara LaskowskaCzechDreamin
 
Connector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a buttonConnector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
 
Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........Alison B. Lowndes
 
Demystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John StaveleyDemystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John StaveleyJohn Staveley
 
Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx
Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptxUnpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx
Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptxDavid Michel
 
SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...
SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...
SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...CzechDreamin
 
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...Product School
 
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...Thierry Lestable
 
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
 
Assuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyesAssuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyesThousandEyes
 
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...CzechDreamin
 
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
 
In-Depth Performance Testing Guide for IT Professionals
In-Depth Performance Testing Guide for IT ProfessionalsIn-Depth Performance Testing Guide for IT Professionals
In-Depth Performance Testing Guide for IT ProfessionalsExpeed Software
 
Measures in SQL (a talk at SF Distributed Systems meetup, 2024-05-22)
Measures in SQL (a talk at SF Distributed Systems meetup, 2024-05-22)Measures in SQL (a talk at SF Distributed Systems meetup, 2024-05-22)
Measures in SQL (a talk at SF Distributed Systems meetup, 2024-05-22)Julian Hyde
 
IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024IoTAnalytics
 
IESVE for Early Stage Design and Planning
IESVE for Early Stage Design and PlanningIESVE for Early Stage Design and Planning
IESVE for Early Stage Design and PlanningIES VE
 

Recently uploaded (20)

ODC, Data Fabric and Architecture User Group
ODC, Data Fabric and Architecture User GroupODC, Data Fabric and Architecture User Group
ODC, Data Fabric and Architecture User Group
 
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024
 
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
 
UiPath Test Automation using UiPath Test Suite series, part 2
UiPath Test Automation using UiPath Test Suite series, part 2UiPath Test Automation using UiPath Test Suite series, part 2
UiPath Test Automation using UiPath Test Suite series, part 2
 
Powerful Start- the Key to Project Success, Barbara Laskowska
Powerful Start- the Key to Project Success, Barbara LaskowskaPowerful Start- the Key to Project Success, Barbara Laskowska
Powerful Start- the Key to Project Success, Barbara Laskowska
 
Connector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a buttonConnector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a button
 
Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........Bits & Pixels using AI for Good.........
Bits & Pixels using AI for Good.........
 
Demystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John StaveleyDemystifying gRPC in .Net by John Staveley
Demystifying gRPC in .Net by John Staveley
 
Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx
Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptxUnpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx
Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx
 
SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...
SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...
SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...
 
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
 
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...
 
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
 
Assuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyesAssuring Contact Center Experiences for Your Customers With ThousandEyes
Assuring Contact Center Experiences for Your Customers With ThousandEyes
 
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
 
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...
 
In-Depth Performance Testing Guide for IT Professionals
In-Depth Performance Testing Guide for IT ProfessionalsIn-Depth Performance Testing Guide for IT Professionals
In-Depth Performance Testing Guide for IT Professionals
 
Measures in SQL (a talk at SF Distributed Systems meetup, 2024-05-22)
Measures in SQL (a talk at SF Distributed Systems meetup, 2024-05-22)Measures in SQL (a talk at SF Distributed Systems meetup, 2024-05-22)
Measures in SQL (a talk at SF Distributed Systems meetup, 2024-05-22)
 
IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024IoT Analytics Company Presentation May 2024
IoT Analytics Company Presentation May 2024
 
IESVE for Early Stage Design and Planning
IESVE for Early Stage Design and PlanningIESVE for Early Stage Design and Planning
IESVE for Early Stage Design and Planning
 

MPEG-7 Services in Community Engines

  • 1. MPEG-7 Services in Community Engines Ralf Klamma Leuven, Belgium October 26, 2007
  • 2.
  • 3.
  • 4.
  • 5.
  • 6.
  • 7. Multimedia management features of MPEG-7 Basis Schema Links&Media Basic Basic tools localization tools data types [IEEE 02] User interaction User preferences Usage History Navigation & Access Index Views Variations Content organization Collections Models Creation & Production Content Management Media Usage Content description Structural aspects Semantic aspects
  • 8. XML Schema Language - Descriptors, DS, and DDL DDL DS DS DS D D D D DS D D Structural aspects of domains Domain spec. MPEG-7 extension MPEG-7 descriptor or DS non MPEG-7 descriptor or DS
  • 9. Schema Tools Basis Schema Links&Media Basic Basic tools localization tools data types [IEEE 02] User interaction User preferences Usage History Navigation & Access Index Views Variations Content organization Collections Models Creation & Production Content Management Media Usage Content description Structural aspects Semantic aspects
  • 12.
  • 13. Annotations <TextAnnotation> <StructuredAnnotation> <Who><Name>Spain</Name</Who> <Where><Name>AC</Name></Where> <When><Name>Mar15</Name></When> </StructuredAnnotation> </TextAnnotation> Structured Annotation <TextAnnotation> <KeywordAnnotation> <Keyword>score</Keyword> <Keyword>Sweden</Keyword> <Keyword>Spain</Keyword> </KeywordAnnotation> </TextAnnotation> Keyword Annotation <TextAnnotation xml:lang=&quot;en-us&quot;> This is a nice apartment. </ TextAnnotation >   <TextAnnotation xml:lang=&quot;en-uk&quot;> This is a nice flat. </TextAnnotation > Free Text Annotation
  • 14. Textual Annotations Score Spain A goal Sweden Against Governer Dependent Governer Dependent Dependent Dependent Dependency structure for &quot;Spain scored a goal against Sweden“
  • 15. Content Management and Description Basis Schema Links&Media Basic Basic tools localization tools data types [IEEE 02] User interaction User preferences Usage History Navigation & Access Index Views Variations Content organization Collections Models Creation & Production Content Management Media Usage Content description Structural aspects Semantic aspects
  • 16. Content Structures – Segment Entities Räumliche und zeitliche Segmente
  • 17. Content Structures – Segment Entities Raum-zeitliches Segment
  • 18. Content Structures – Segment Decomposition Segment decomposition
  • 19.
  • 20. Example for Segmentation Tree Foreground Background SR1: · Creation, Usage meta information · Media description · Textual annotation · Color histogram, Texture SR2: · Shape · Color Histogram · Textual annotation SR6: · Color Histogram · Textual annotation SR5: · Shape · Textual annotation SR4: · Shape · Color Histogram · Textual annotation SR3: · Shape · Color Histogram · Textual annotation
  • 21. Example for Content Semantics Segment Tree Shot1 Shot2 Shot3 Segment 1 Sub-segment 1 Sub-segment 2 Sub-segment 3 Sub-segment 4 segment 2 Segment 3 Segment 4 Segment 5 Segment 6 Segment 7 Semantic DS (Events) • Introduction • Summary • Program logo • Studio • Overview • News Presenter • News Items • International • Clinton Case • Pope in Cuba • National • Twins • Sports • Closing Time Axis
  • 22. Putting it all together
  • 23. Navigation and Access Basis Schema Links&Media Basic Basic tools localization tools data types [IEEE 02] User interaction User preferences Usage History Navigation & Access Index Views Variations Content organization Collections Models Creation & Production Content Management Media Usage Content description Structural aspects Semantic aspects
  • 24. Summaries – Keyframes Original Conten (represented by Keyframes) and highlighted summary content MovieClip1 Summary MovieClip2 MovieClip3
  • 25. Hierarchical Summary Hierarchical Summary Summary Theme List Summary SegmentGroup Summary Segment 0, 1 1, * 1, * 0, *
  • 26. Sequential Summary Sequential Summary Visual SummaryComponent Audio SummaryComponent Textual SummaryComponent 0, * 0, * 0, *
  • 27. Views Multimedia program Multimedia program View Filtering Partition Region View Signal Source Signal View graphs View trees View sets Source Target View decompositions
  • 28. Views – Space and Frequency Graph F F F S S S
  • 29. Variations Variation Set Multimedia program Variation Fidelity Relationship Priority Multimedia program Variation Fidelity Relationship Priority Multimedia program Image Video Video Source Variation Variation
  • 30. Content Organization Basis Schema Links&Media Basic Basic tools localization tools data types [IEEE 02] User interaction User preferences Usage History Navigation & Access Index Views Variations Content organization Collections Models Creation & Production Content Management Media Usage Content description Structural aspects Semantic aspects
  • 31. Collections Collection (abstract) Segment collection Content collection Descriptor collection Concept collection Mixed collection Collection structure
  • 32. Content Collections and Collection Structure Different collection can be combined according to their collection structure Collection A Collection B Collection C R ac R bc R ab
  • 33.
  • 34. Cluster Model – Relevance Feedback After relevant content is marked by the user, the retrieval system can deliver more precise content clusters
  • 35. State Transition Models State Transition models can be used for summarizing or classifying transitions of events on the timeline of a video sequence Video sequence with events, e.g. staging of an actor A C B p ab p ac p bc p ca Label Scene A C B Event A Event B Event C
  • 36. User Interaction Basis Schema Links&Media Basic Basic tools localization tools data types [IEEE 02] User interaction User preferences Usage History Navigation & Access Index Views Variations Content organization Collections Models Creation & Production Content Management Media Usage Content description Structural aspects Semantic aspects
  • 37. Multimedia System with User Interaction Content filter & search engine Content browsing engine User profiling engine Local multimedia system Multimedia content description Multimedia content Multimedia content description Multimedia content description User preferences User action history Other devices Content/service provider User
  • 38. Usage History Usage history 1, * 0, * UserIdentifier User action history Observation period User action list ActionType Action data item User action ProgramIdentifier ActionTime 1, * 1, * 0, *
  • 39. User Preferences User preferences UserIdentifier Browsing preferences Summary preferences Preference condition Filtering and search preferences Preference condition Classification preferences Creation preferences Source preferences 0, * 0, * 0, * 0, * 0, * 0, * 0, * 0, * 0, *
  • 40. Mapping Usage Hisotries on User Preferences Usage history description UserAction Program ID 1 UserAction Program ID 2 Content description Program ID 1 Title 1 Genre A Content description Program ID 2 Title 2 Genre B User preference description Classification Preferences Genre A preference Value a Genre B preference Value b
  • 41.
  • 45. Texture Browsing Descriptor II Directions of textures:
  • 47.
  • 48.
  • 49.
  • 51.
  • 52. LAS – Architecture Overview Data Sources Context-Aware Services Community Engine WWW MPEG-7 Services Context Services User Manager Map Services Storytelling Service Object Manager (Mobile) Interfaces Session Manager SNA Tools Multimedia Processor Multimedia Annotation Multimedia Extractor Multimedia Adaptation Multimedia Player Metadata Databases Connectors: HTTP, SOAP Multimedia Repository Media Creation Media Search Media Tagging Semantic Browsing Mashups Automatic Discovery & Configuration Multimedia Input Data Access Multimedia Repository Multimedia Repository Invoking services Data flows
  • 53. Data Sources Context-Aware Services Community Engine WWW MPEG-7 Services Context Services User Manager Map Services Storytelling Service Object Manager (Mobile) Interfaces Session Manager SNA Tools Multimedia Processor Multimedia Annotation Multimedia Extractor Multimedia Adaptation Multimedia Player Metadata Databases Connectors: HTTP, SOAP Multimedia Repository Media Creation Media Search Media Tagging Semantic Browsing Mashups Automatic Discovery & Configuration Multimedia Input Data Access Multimedia Repository Multimedia Repository MPEG-7 Services Context Services Media Creation GPS-augmented multimedia creation Multimedia GIS Map Services Media Search Semantic Browsing MPEG-7 Services Context aware multimedia GIS Map Services Media Search Semantic Browsing Context Services MPEG-7 Services MPEG-7 multimedia tagging and commsonomy SNA Tools Media Search Media Tagging MPEG-7 Services MPEG-7 Services Context Services Media Search Semantic Browsing MPEG-7 enabled context aware multimedia search MPEG-7 Services Storytelling Service Semantic Browsing Non-linear digital storytelling Storytelling Service Storytelling on the ipod Context aware multimedia search Media Search MPEG-7 Services Context Services
  • 54.
  • 55.
  • 57.